Behavior tree library with a fluent API
A Behavior Tree implementation in modern Javascript
ECS-based AI behavior tree system - works with any ECS framework (ESEngine, Cocos, Laya, etc.)
Behavior Tree Component for Croquet Worldcore
Behavior Tree library focusing on async functions
Behavior tree, written in typescript.
behavior tree
A behavior tree implementation.
Behavior tree library with a fluent API, compiled for the browser
Behavior tree library with a fluent API
Behavior Tree for Javascript
Behavior Tree Studio server
behavior tree engine
Behavior Tree framework for TypeScript/JavaScript — simplifies game AI, skills, and buff logic.
Behavior Tree Studio UI
Behavior tree library with a fluent API, compiled for the browser
A JavaScript behavior tree library for easily creating and managing complex behavior patterns in game development.
JavaScript implementation of a modular behavior tree
A Behavior Tree library in TypeScript.
Optional dependency of async-behavior-tree that allows live debugging using Groot via zmq.
CLI for Behavior Tree Studio
behavior tree visual editor(using Konva)
A behavior tree implementation that separates model logic from action implementation and provides behavior-tree-as-a-service. Try the [interactive demo](http://0xABAD.github.io/behavior_tree). This is obviously based on [Dan Abad](https://github.com/0xABA
Small, no-dependency javascript behavior tree engine to run game/simulation AI.
Yet another behavior tree library for rust!
Behavior tree plugin for Bevy.
Behavior tree framework with a runtime, plugin system, and Beehive editor.
Beetry library with reusable channel implementations.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
Internal beetry crate. For the public API, check the beetry crate.
A robust and customizable Ruby gem for creating Behavior Trees.
behavior trees for ruby
A behavior tree library for ruby.
Tree behavior for ActiveRecord models and Mongoid documents.
Jumoku provides you with tree behaviors to mixin and tree classes to inherit from. Raw tree, common binary trees, custom trees...
Tree-sitter-backed TOML substrate behavior for the Structured Merge TOML family.
Syntax Tree aligns arguments of parens-less method calls. This plugin disables that behavior.
All .erb files in the specified directory tree are going to be evaluated. The corresponding non.erb files are going to be written by removing the .erb extension. See the features/*.feature files for the expected behavior.
Behavioral spec-based task management with compact IDs, subtask trees, AI-powered implementation plans, and automated health checks. Same CLI for developers and coding agents.
In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.
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